During the course of study, students participate in a range of surveys which are conducted to enable the University to evaluate the quality of teaching and learning, and seek direct input to improve the student experience.

Students are invited to answer a range of questions, including a number of open-ended questions, which enable them to share their views in the form of comments. In the Student Experience of Course survey, students provide up to 55,000 comments each trimester. In order to use this extremely valuable information, a specific analytical technique, known as text mining, is applied to identify meaningful information and themes from the unstructured comments. While on a smaller scale, our work resembles that of Griffith's Big Data and Smart Analytics Lab, led by Professor Bela Stantic, which uses a much greater volume and variety of social media sources to identify important social beliefs.

With this in mind, the Advanced Analytics team has started a project to analyse qualitative feedback in order to gain additional insights into students' experiences of courses and teaching.

This 'text mining' project includes: 


                   

An example of the type of information provided is shown in the figure below:

                       

New retention risk predictions for international students
We are currently working with Griffith International to create a model for identifying students at risk of leaving, using factors that are relevant for international students. In addition to variables used for domestic student risk predictions, this model includes:

• the agent an international student has
• the country of origin
• home country gross national product (GNP) as an economic measure
• exchange rates

To date, this work indicates that the agent and home country are significant factors in determining the risk of an international student leaving study. Further analysis on these two important factors will be published soon.

Further information may be obtained by contacting Clancy Birrell, Manager, Advanced Analytics on ext. 58073, or c.birrell@griffith.edu.au.

Ever wonder how the Advanced Analytics team contributes to the University? Clancy Birrell, Advanced Analytics Manager, has been very busy showcasing the work of his team in and outside of the University.

During a typical presentation, Clancy answers questions on machine learning algorithms, how to set and plan metrics for KPIs and measurement, new analytical approaches as well as opportunities for collaboration with our area.

The Advanced Analytics team continue to increase their engagement with areas across the University to assist in expanding analytical capabilities and to develop evidence-based strategies for key decision making processes.

Preliminary results show Griffith has recorded an improvement (up +3.1%) in full-time employment rates for domestic undergraduate students, to 65.7% in 2017. Once benchmarked data is released, we will be bringing the University another GOS infographic to summarise our results. You can access our Media and Publications page to view published infographics.

In addition to the GOS, the Graduate Outcomes Survey Longitudinal (GOS-L) is now running. The 2017 GOS-L supplements the Graduate Outcomes Survey by measuring the medium-term employment outcomes of higher education graduates, approximately three years after they have completed their study. The 2017 GOS-L reports on domestic undergraduate students who completed in 2014. This longitudinal research shows:

• In 2013, 65.3% of students surveyed were in full-time employment.
• Three years on, the rate of employment for this group of students has increased to 90.6%.

You can locate more great findings about the labour market outcomes of graduates across the nation on the Quality Indicators for Learning and Teaching website.

The Researcher Profile is a valuable tool that profiles Griffith researchers and provides a one-stop summary of their income, publications, and HDR supervision and completions. This report has been accessed extensively during the recent Academic Staff Career Development (ASCD) process and we've received a lot of feedback on its use and possible improvement. In the past, the Profile has included only Higher Education Research Data Collection (HERDC) eligible income and publications, and only finalised data for the previous calendar year. Reporting will be enhanced over the coming months to include all publications and income to date recorded in the Griffith Research Information Management System (RIMS), and so will be a more comprehensive resource for researchers and supervisors in the future.

If you do choose to visit and review the information currently in the Researcher Profile, three simple areas to look out for are:

• Is your PhD year correct? This will impact on your ECR status.
• Are all your prior year publications correct, including those from previous institutions? Publications will not appear on the Profile unless they are captured in the RIMS. The process for advising us of missing publications can be found via this link. However, remember Griffith no longer records non-ERA eligible outputs in the RIMS. 
• Does your HDR supervision status appear to be correct? Please check your current HDR candidate supervision listing. This is live data currently recorded in the PeopleSoft system.

Any queries you might have in relation to the Researcher Profile can be directed to us at bi-info@griffith.edu.au